AI-102 – Microsoft Azure AI Engineer

Training Title: AI-102 – Microsoft Azure AI Engineer

Course Summary

The AI-102: Microsoft Azure AI Engineer training is designed for IT professionals who want to specialize in creating and managing artificial intelligence (AI) solutions on the Microsoft Azure platform. This course prepares you to design, develop, and deploy AI models and cognitive services on Azure. You will learn to work with tools such as Azure Cognitive Services, Azure Machine Learning, and Azure Bot Services to build robust and scalable AI solutions. It is ideal for those aiming for the Microsoft Certified: Azure AI Engineer Associate certification.

Training Objectives

• Design AI solutions on Microsoft Azure using cognitive services and machine learning.
• Develop, train, and deploy machine learning models using Azure Machine Learning.
• Build intelligent solutions by integrating services like Azure Cognitive Services for image recognition, speech transcription, and text analysis.
• Implement chatbots and conversational solutions through Azure Bot Services.
• Learn how to work with APIs and cloud services for AI integration into enterprise applications.
• Prepare for the AI-102 exam to achieve the Microsoft Certified: Azure AI Engineer Associate certification.

Training Program

Day 1: Introduction to Artificial Intelligence on Azure

1. Overview of Azure AI Services
   • Introduction to Azure Cognitive Services, Azure Machine Learning, and Azure Bot Services.
   • Understanding the fundamentals of artificial intelligence, machine learning, and deep learning.
   • Role of an AI Engineer and responsibilities in creating AI solutions on Azure.

Day 2: Designing and Developing AI Solutions with Azure Cognitive Services

2. Using Cognitive Services
   • Utilize Computer Vision, Speech Services, and Language Understanding (LUIS) to add cognitive capabilities to applications.
   • Implement image and video recognition, speech transcription and translation, and text analysis.
   • Build models to extract information from images, text, and voice.

Day 3: Developing and Managing Machine Learning Models

3. Using Azure Machine Learning
   • Create, train, deploy, and manage machine learning models with Azure Machine Learning.
   • Understand the machine learning lifecycle, including data collection, preparation, training, and model deployment.
   • Set up and manage training environments and data pipelines.
   • Use Azure Databricks for complex data analysis and processing.

Day 4: Creating Conversational Solutions with Azure Bot Services

4. Building Chatbots with Azure Bot Services
   • Introduction to Azure Bot Services and the Bot Framework SDK for building conversational interfaces.
   • Develop intelligent chatbots to interact with users across various channels (websites, mobile apps, etc.).
   • Implement QnA Maker and integrate LUIS for natural language processing (NLP).

Day 5: Deploying, Monitoring, and Securing AI Solutions

5. Deploying and Monitoring AI Solutions
   • Deploy AI models on Azure Kubernetes Service (AKS) and other cloud services for scalable solutions.
   • Use Azure Monitor to track performance and behavior of AI models in production.
   • Set up tracking and analysis of results to optimize solution performance.
6. Security and Privacy in AI Solutions
   • Implement best practices for securing AI applications and ensuring data privacy.
   • Ensure compliance with regulations like GDPR.
   • Use Azure security tools to protect AI models.
7. Preparing for the AI-102 Exam
   • Review key concepts and technical skills covered during the training.
   • Tips and strategies for passing the AI-102 exam and achieving the Microsoft Certified: Azure AI Engineer Associate certification.
   • Practice exam questions and simulations to prepare for certification.

Training Details

• Duration: 5 days (40 hours), combining theoretical lessons, practical demonstrations, and interactive exercises.
• Prerequisites:
  • Prior experience with Azure services, including resource management and working in the Azure Portal.
  • Basic knowledge of machine learning and AI technologies.
  • Development skills, ideally in Python, and experience with tools like Jupyter Notebook.
• Target Audience:
  • Cloud application developers, AI and machine learning engineers, and data professionals.
  • Anyone looking to specialize in AI on Microsoft Azure and earn the Azure AI Engineer Associate certification.

Certification

This training prepares you for the AI-102 exam and the Microsoft Certified: Azure AI Engineer Associate certification.

Scale your AI skills across the enterprise with Microsoft Azure and create intelligent solutions that will transform your organization!